Ting Zhang 张婷

Find me @
Research Scientist @ Singapore Management University (SMU)

Email: happygirlzt@gmail.com


About Me

My name is Ting Zhang, a.k.a., happygirlzt. I have worked as a research scientist at SMU since Feb 2024. The research project I am working on is about detecting software vulnerabilities using large language models. Prior to this, I defended my doctoral dissertation titled "Supporting Software Engineers with Large Language Model-Based Automation" on 13 Dec 2023. I was fortunate to be advised by Prof. David Lo and Prof. Lingxiao Jiang.

Academic Qualifications

Publications

    * indicates I am the corresponding author.

    Journal Papers

  • [J3] [TOSEM 2024] Revisiting Sentiment Analysis for Software Engineering in the Era of Large Language Models
    Ting Zhang, Ivana Clairine Irsan, Ferdian Thung, David Lo
    [PDF] [Code]

  • [J2] [TOSEM 2023] Representation Learning for Stack Overflow Posts: How Far are We?
    Junda He, Xin Zhou, Bowen Xu, Ting Zhang, Kisub Kim, Zhou Yang, Ivana Clairine Irsan, Ferdian Thung, David Lo
    [PDF] [Code]

  • [J1] [TOSEM 2023, ASE 2023 Journal First] Duplicate Bug Report Detection: How Far Are We?
    Ting Zhang, DongGyun Han, Venkatesh Vinayakarao, Ivana Clairine Irsan, Bowen Xu, Ferdian Thung, David Lo, Lingxiao Jiang
    [PDF] [Code]

  • Conference Papers

  • [C11] [ASE 2024] ChatBR: Automated assessment and improvement of bug report quality using ChatGPT
    Lili Bo, Wangjie Ji, Xiaobing Sun, Ting Zhang, Xiaoxue Wu, Ying Wei
    [PDF] [Code]

  • [C10] [FORGE 2024 New Idea] On Evaluating the Efficiency of Source Code Generated by LLMs
    Changan Niu, Ting Zhang, Chuanyi Li, Bin Luo, Vincent Ng
    [PDF] [Code]

  • [C9] [ICSE 2024 NIER] Large Language Model for Vulnerability Detection: Emerging Results and Future Directions
    Xin Zhou, Ting Zhang, David Lo
    [PDF] [Code]

  • [C8] [MSR 2023] PICASO: Enhancing API Recommendations with Relevant Stack Overflow Posts
    Ivana Clairine Irsan, Ting Zhang*, Ferdian Thung, Kisub Kim, David Lo
    [PDF] [Code]

  • [C7] [SANER 2023] Multi-Modal API Recommendation
    Ivana Clairine Irsan, Ting Zhang*, Ferdian Thung, Kisub Kim, David Lo
    [PDF] [Code]

  • [C6] [FSE 2022 Demo] iTiger: An Automatic Issue Title Generation Tool
    Ting Zhang, Ivana Clairine Irsan, Ferdian Thung, David Lo, Lingxiao Jiang
    [PDF] [Code]

  • [C5] [FSE 2022 Demo] CodeMatcher: A Tool for Large-Scale Code Search Based on Query Semantics Matching
    Chao Liu, Xuanlin Bao, Xin Xia, Meng Yan, David Lo, Ting Zhang.
    [PDF] [Code]

  • [C4] [ASE 2022] Summarization for Technical Queries: Benchmark and New Approach
    Chengran Yang, Bowen Xu, Ferdian Thung, Yucen Shi, Ting Zhang, Zhou Yang, Xin Zhou, Jieke Shi, Junda He, DongGyun Han, David Lo
    [PDF] [Code]

  • [C3] [ICSME 2022] Automatic Pull Request Title Generation
    Ting Zhang, Ivana Clairine Irsan, Ferdian Thung, DongGyun Han, David Lo, Lingxiao Jiang
    [PDF] [Code]

  • [C2] [ICPC 2022] Benchmarking Library Recognition in Tweets
    Ting Zhang, Divya Prabha Chandrasekaran, Ferdian Thung, David Lo
    [PDF] [Code]

  • [C1] [ICSME 2020] Sentiment Analysis for Software Engineering: How Far Can Pre-trained Transformer Models Go?
    Ting Zhang, Bowen Xu, Ferdian Thung, Stefanus Agus Haryono, David Lo, Lingxiao Jiang
    [PDF] [Code]

Pre-print (Under Journal Submission)

  • Evaluating Pre-trained Language Models for Repairing API Misuses
    Ting Zhang, Ivana Clairine Irsan, Ferdian Thung, David Lo, Asankhaya Sharma, Lingxiao Jiang
    [PDF]

  • Cupid: Leveraging ChatGPT for More Accurate Duplicate Bug Report Detection
    Ting Zhang, Ivana Clairine Irsan, Ferdian Thung, David Lo
    [PDF]

  • Explaining Explanation: An Empirical Study on Explanation in Code Reviews
    Ratnadira Widyasari, Ting Zhang, Abir Bouraffa, Walid Maalej, David Lo
    [PDF]

  • LLM-Enhanced Static Analysis for Precise Identification of Vulnerable OSS Versions
    Yiran Cheng, Lwin Khin Shar, Ting Zhang, Shouguo Yang, Chaopeng Dong, David Lo, Shichao Lv, Zhiqiang Shi, Limin Sun
    [PDF]

Teaching

  • I was a teaching assistant for
    • IS706: Software Mining and Analysis (2022 Spring, SMU)
    • Probability & Mathematical Statistics (2017 Summer, SYSU)
    • Discrete Mathematics (2016 Summer, SYSU)
  • I occasionally teach algorithms in YouTube, where I proudly have 13k+ subscribers.
  • I was a part-time instructor at a software engineering training company, teaching algorithm courses five times from 2021 to 2023. I have helped 30+ students find software developer jobs in the US.

Talks

  • 22 Nov 2023, Automatic Program Repair event at National University of Singapore, Repairing API misuse
  • 20 Nov 2023, North Carolina State University, Large Langague Models for Sentiment Analysis in Software Engineering

Internship

  • Veracode: Repairing API misuse bugs. May - August 2022

Services

Selected Honors & Awards

SMU Presidential Doctoral Fellowship in Computing, AY2023/2024.
Full Scholarship for the Ph.D. study, 2020 - 2023.
Second-class Scholarship in SYSU, AY2015/2016.

Misc

I enjoy cycling, running, and swimming. I also love playing the sports games on Nintendo Switch. I was a member of the SMU Aquathlon team and the SYSU rowing team. During my undergraduate studies, I was fortunate to represent SYSU in several national and international-level rowing competitions. Check out the moments.